Data Scientist at Envestnet, Inc

Posted 6 months ago
Bengaluru, Karnataka
Rs15,000 - Rs15,000 per month
Application deadline closed.

Job Description

Data Scientist

Envestnet, Inc


What We Have

Envestnet Data Intelligence (EDI) Group is driving innovations using the latest Machine Learning algorithms and Big Data Engineering frameworks at Envestnet. We have a high-caliber, focused and a mission-driven culture for our teams. Data Science work is challenging and rewarding as the Machine Learning models we build have to meet accuracy SLAs, be scalable to run on petabytes of data and parallelizable to run on distributed computing infrastructure. The insights we derive from the financial data matters to crucial cutting-edge business decisions made across the global financial services firms every day and solves real world problems. We are leveraging our deep expertise in financial data to launch innovative solutions into the Financial Services Industry. This role involves working closely with teams both within India in the US.

Envestnet is also recognized as Top 10 best places to work for Data Sciences in India- link.

What We Need From You
• You need… to be a thinker. We are looking for a very curious data scientist who enjoys a deep dive into the raw data to help figure out the right set of questions and find the answers to those questions.
• You also need to be a doer. You will be responsible for hands-on data cleansing, transformation and creating predictive models and classifiers.
• You need to be smart and build smart products. A big part of this job is about creating actionable insights for our customers and the business using machine learning and statistical techniques. Translate analytic insights into concrete, actionable recommendations for business or product improvement.
• You need to be ambitious. You must be passionate about applying mathematical modeling to solve real world problems. You must be willing to work with a team of modelers on cutting-edge prediction techniques who knows the best practices around modeling and validation. And more than anything, you must love to turn ideas into reality. If you are the happiest when you can prove the impact of statistical models/machine learning in generating business impact, let us know.

Required Skills & Experience

(Various roles open from Data Scientist, Senior Data Scientist to Associate Data Scientist, role will depend on educational qualifications, past experience and performance during the interview)
• 2-5 years of experience in the area of data science/machine learning specializing in a relevant field such as Probability, Statistics, Machine Learning, Data Mining, Artificial intelligence/Computer Science.
• Solid programming skills in Python, ML frameworks (e.g., scikit-learn, tensorflow, nltk, sagemaker), Shell Programming and SQL.
• Deep understanding of statistical modelling/machine learning/ data mining concepts
• Strong analytical and quantitative problem solving ability
• Strong interpersonal and communication skills: ability to tell a clear, concise, actionable story with data, to folks across various levels of the company.

Preferred Skills & Experience
• Experience in any one of the following industries: Financial Markets/Wealth Management, Retail and Banking industries.
• Experience in working with huge datasets and big data technologies.
• Experience with Natural Language Processing/Text Analytics

Role And Responsibilities (Data Scientist / Sr. Data Scientist)
• Work independently or in team to solve complex problems and create scalable models/algorithms that will be integrated into Envestnet’s tools and products.
• Come up with actionable ideas to solve problems faced by product managers & senior leadership then implement those ideas.
• Communicate context, data, solution and implications to the team, senior leaders and stakeholders.

Qualifications And Experience
• Post-Graduate (preferred)/Undergraduate degree in Data Science/Computer Science/ Mathematics/ Statistics/ Economics or MBA Finance/Data Science from premier schools.
• 2-5 years of experience in applying data science technique to real world problems